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Clonal hematopoiesis (CH) results from somatic genomic alterations that drive clonal expansion of blood cells. Somatic gene mutations associated with hematologic malignancies detected in hematopoietic cells of healthy individuals, referred to as CH of indeterminate potential (CHIP), have been associated with myeloid malignancies, while mosaic chromosomal alterations (mCAs) have been associated with lymphoid malignancies. Here, we analyzed CHIP in 55,383 individuals and autosomal mCAs in 420,969 individuals with no history of hematologic malignancies in the UK Biobank and Mass General Brigham Biobank. We distinguished myeloid and lymphoid somatic gene mutations, as well as myeloid and lymphoid mCAs, and found both to be associated with risk of lineage-specific hematologic malignancies. Further, we performed an integrated analysis of somatic alterations with peripheral blood count parameters to stratify the risk of incident myeloid and lymphoid malignancies. These genetic alterations can be readily detected in clinical sequencing panels and used with blood count parameters to identify individuals at high risk of developing hematologic malignancies. Genomic analyses in the UK Biobank show that clonal hematopoiesis of indeterminate potential in the lymphoid lineage is associated with a higher risk of developing lymphoid malignancies

Clonal hematopoiesis of indeterminate potential (CHIP) and mosaic chromosomal alterations (mCAs) represent two forms of clonal hematopoiesis where clones bearing expanded somatic mutations have been linked to both oncologic and non-oncologic clinical outcomes including atherosclerosis and all-cause mortality. Epidemiologic studies have highlighted smoking as an important driver of somatic mutations across multiple tissues. However, establishing the causal role of smoking in clonal hematopoiesis has been limited by observational study designs, which may suffer from confounding and reverse-causality. We performed two complementary analyses to investigate the role of smoking in mCAs and CHIP. First, using an observational study design among UK Biobank participants, we confirmed strong associations between smoking and mCAs. Second, using two-sample Mendelian randomization, smoking was strongly associated with mCA but not with CHIP. Overall, these results support a causal association between smoking and mCAs and suggest smoking may variably shape the fitness of clones bearing somatic mutations.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk.

Somatic mutations in blood indicative of clonal hematopoiesis of indeterminate potential (CHIP) are associated with an increased risk of hematologic malignancy, coronary artery disease, and all-cause mortality. Here we analyze the relation between CHIP status and incident peripheral artery disease (PAD) and atherosclerosis, using whole-exome sequencing and clinical data from the UK Biobank and Mass General Brigham Biobank. CHIP associated with incident PAD and atherosclerotic disease across multiple beds, with increased risk among individuals with CHIP driven by mutation in DNA Damage Repair (DDR) genes such as and . To model the effects of DDR-induced CHIP on atherosclerosis, we used a competitive bone marrow transplantation strategy, and generated atherosclerosis-prone -/- chimeric mice carrying 20% p53-deficient hematopoietic cells. The chimeric mice were analyzed 13-weeks post-grafting and showed increased aortic plaque size and accumulation of macrophages within the plaque, driven by increased proliferation of p53-deficient plaque macrophages. In summary, our findings highlight the role of CHIP as a broad driver of atherosclerosis across the entire arterial system beyond the coronary arteries, and provide genetic and experimental support for a direct causal contribution of TP53-mutant CHIP to atherosclerosis.

Advances in nanomedicine are providing sophisticated functions to precisely control the behavior of nanoscale drugs and diagnostics. Strategies that coopt protease activity as molecular triggers are increasingly important in nanoparticle design, yet the pharmacokinetics of these systems are challenging to understand without a quantitative framework to reveal nonintuitive associations. We describe a multicompartment mathematical model to predict strategies for ultrasensitive detection of cancer using synthetic biomarkers, a class of activity-based probes that amplify cancerderived signals into urine as a noninvasive diagnostic. Using a model formulation made of a PEG core conjugated with protease-cleavable peptides, we explore a vast design space and identify guidelines for increasing sensitivity that depend on critical parameters such as enzyme kinetics, dosage, and probe stability. According to this model, synthetic biomarkers that circulate in stealth but then activate at sites of disease have the theoretical capacity to discriminate tumors as small as 5 mm in diameter—a threshold sensitivity that is otherwise challenging for medical imaging and blood biomarkers to achieve. This model may be adapted to describe the behavior of additional activity-based approaches to allow cross-platform comparisons, and to predict allometric scaling across species.

Rare genetic mutations that disrupt the functionality of important genes increase the risk of psychiatric and neurodevelopmental disorder. This study found that, in the general population not diagnosed with such disorders, these same mutations affect the average educational level. Carriers of these mutations have on average half a semester less of education than noncarriers. Disruptive, damaging ultra-rare variants in highly constrained genes are enriched in individuals with neurodevelopmental disorders. In the general population, this class of variants was associated with a decrease in years of education (YOE). This effect was stronger among highly brain-expressed genes and explained more YOE variance than pathogenic copy number variation but less than common variants. Disruptive, damaging ultra-rare variants in highly constrained genes influence the determinants of YOE in the general population.

Less than 3% of protein-coding genetic variants are predicted to result in loss of protein function through the introduction of a stop codon, frameshift, or the disruption of an essential splice site; however, such predicted loss-of-function (pLOF) variants provide insight into effector transcript and direction of biological effect. In >400,000 UK Biobank participants, we conduct association analyses of 3759 pLOF variants with six metabolic traits, six cardiometabolic diseases, and twelve additional diseases. We identified 18 new low-frequency or rare (allele frequency < 5%) pLOF variant-phenotype associations. pLOF variants in the gene GPR151 protect against obesity and type 2 diabetes, in the gene IL33 against asthma and allergic disease, and in the gene IFIH1 against hypothyroidism. In the gene PDE3B , pLOF variants associate with elevated height, improved body fat distribution and protection from coronary artery disease. Our findings prioritize genes for which pharmacologic mimics of pLOF variants may lower risk for disease. Examination of predicted loss-of-function (pLOF) genetic variants allows direct identification of genes with therapeutic potential. Here, Emdin et al. perform association analysis for 3759 pLOF variants with 24 traits and highlight protective variants against cardiometabolic and immune phenotypes.

Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high-coverage whole-genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional 14,904 samples. Using up to 7,134 samples with available phenotype data, our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic datasets provided evidence for causal mechanisms at several loci, including at a previously undiscovered basophil count-associated locus near the master hematopoietic transcription factor CEBPA. The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.

The importance of 1,5‐anhydroglucitol (1,5‐AG) as an intermediate biomarker for diabetic pregnancy is multi‐fold: (1) it serves as a reliable indicator of moderate‐level glycemic control, especially during early gestation; (2) it has been associated with increased risk of diabetes, independent of HbA1c and fasting glucose; and (3) it is an independent risk factor for the development of eclampsia during pregnancy. However, the clinical use of this biomarker during pregnancy has been underutilized due to physiological changes in glomerular filtration rate, plasma volume, and other hemodynamic parameters which have been hypothesized to bias gestational serum 1,5‐AG concentrations. Here, we develop an in‐silico model of gestational 1,5‐AG by combining pre‐existing physiological data in the literature with a two‐compartment mathematical model, building off of a previous kinetic model described by Stickle and Turk () Am. J. Physiol., 273, E821. Our model quantitatively characterizes how renal and hemodynamic factors impact measured 1,5‐AG during normal pregnancy and during pregnancy with gestational diabetes and diabetes mellitus. During both normal and diabetic pregnancy, we find that a simple two‐compartment model of 1,5‐AG kinetics, with all parameters but reabsorption fraction adjusted for time in pregnancy, efficiently models 1,5‐AG kinetics throughout the first two trimesters. Allowing reabsorption fraction to decrease after 25 weeks permits parameters closer to expected physiological values during the last trimester. Our quantitative model of 1,5‐AG confirms the involvement of hypothesized renal and hemodynamic mechanisms during pregnancy, clarifying the expected trends in 1,5‐AG to aid clinical interpretation. Further research and data may elucidate biological changes during the third trimester that account for the drop in 1,5‐AG concentrations, and clarify physiological differences between diabetes subtypes during pregnancy. The importance of 1,5‐anhydroglucitol (1,5‐AG) as an intermediate biomarker for diabetic pregnancy is multi‐fold: (1) it serves as a reliable indicator of moderate‐level glycemic control, especially during early gestation; (2) it has been associated with increased risk of diabetes, independent of HbA1c and fasting glucose; and (3) it is an independent risk factor for the development of eclampsia during pregnancy. However, the clinical use of this biomarker during pregnancy has been underutilized due to physiological changes in glomerular filtration rate, plasma volume, and other hemodynamic parameters which have been hypothesized to bias gestational serum 1,5‐AG concentrations. Here, we develop an in‐silico model of gestational 1,5‐AG by combining pre‐existing physiological data in the literature with a two‐compartment mathematical model, quantitatively characterizing how renal and hemodynamic factors impact measured 1,5‐AG during normal pregnancy and during pregnancy with gestational diabetes and diabetes mellitus.

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown 1 . The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer 2 – 4 and coronary heart disease 5 —this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP) 6 . Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues. Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.